EXPLORING THE SUB DIMENSIONS OF PERCEIVED OVER …djsronline.in/Downloads/Vlolume5/2.pdf ·...

De Paul Journal of Scientific Research 5 (1) March 1, 2018 ISSN 2394-4412

20

EXPLORING THE SUB DIMENSIONS OF PERCEIVED

OVER-QUALIFICATION

M. Bhasi* & Razeena Rasheed**

Abstract This study discusses the significance of studying over qualification and attempts

to measure and explore the sub dimensions of perceived over qualification. Over

qualification is a phenomenon resulting in the possession of higher educational

qualifications by employees than what their job demands. The conduct of this

study is found relevant because over qualification results in negative work

attitudes among employees. The impact of over qualification is seemed to be

more dismal when it is subjective. The primary reason behind over qualification

is reported to be labor market imperfections resulting in oversupply of graduates

and concentration of certain skills in the labor market. Perceived over

qualification is the subjective aspect of over qualification and explores the

individual’s interpretations of their employment situations, focusing on their

perceptions regarding use of their skills and abilities. The study reviews various

existing measures for measuring perceived over qualification. The construct is

measured by adapting statements from different existing scales of perceived over

qualification. An exploratory factor analysis has been performed and three

dimensions were explored namely excess education, excess skills and excess

experience explaining 73% of variance.

Introduction

Over-qualification is a phenomenon resulting in the possession of higher

educational qualifications by employees than what their job demands.

Educational mismatch is of a serious concern as it results in employee

frustrations, job dissatisfactions, less organizational performance, less

productivity, increased labor turnover etc. It may even lead to

psychological problems hindering the employee wellbeing and thereby

organizational effectiveness. The primary reason behind over-qualification

* Professor and Dean, School of Management Studies, CUSAT ** FDP Substitute Lecturer, Department of Economics, Al Ameen College, Aluva


21

is reported to be labor market imperfections resulting in oversupply of

graduates and concentration of certain skills in the labor market.

According to Black (2012) spending on education can be considered as an

investment. Hence Individuals evaluate the returns to their education

through the employment they achieve. Labor markets also critically

evaluate such investments and the results are often interpreted through

increased earnings, high labor force participation rates, increased worker

productivity etc. This is done because labor market failures can negatively

affect the returns that accrue to individuals and societies. The labor market

failures are often judged through the failure to facilitate the full utilization

of human capital attained through education. This happens due to market

imperfections where firms are not in a position to adjust jobs so as to fully

utilize the human capital of employees and so long as the employees are

willing to accept jobs for which they are overeducated.

Berg (1971) pointed out that the expansion of education may have

unintended and negative consequences for society. He argued that

employers' increased reliance on education credentials of employees may

place severe limitations on the achievement of disadvantaged groups.

Individuals acquiring higher qualifications expect an “appropriate type of

work” upon completing their education. This appropriate type of job might

not be simply a high paying job but rather the one with a right kind of

income, working conditions, associates and identity etc. Thus a lack of fit

in the labor market can lead to a cognitive dissonance and dissatisfaction

when the worker find himself in a position “beneath” that for which he was

prepared..

Over-qualification can be understood under two main perspectives –

objective and subjective (Khan & Marrow, 1991). Objective over-


22

qualification use accepted standards to determine whether an employee is

overqualified or not. The objective aspect is defined in terms of the level

of utilization of individuals’ human capital, in comparison to an accepted

standard of their referent group, for example other individuals with similar

qualifications (Feldman, 1996).

Perceived over qualification

Perceived over-qualification is the subjective aspect of over-qualification

and explores the individual’s interpretations of their employment

situations, focusing on their perceptions regarding use of their skills and

abilities (Khan & Marrow, 1991; Jones Johnson & Johnson, 1995). Thus

over-qualification is much more likely to reflect the underutilization of

skills and it is generally termed as over-qualification in the literature

(Green, McInthosh, & Vignoles, 1999).

Perceived over-qualification is defined as the extent to which an employed

individual perceives that he or she (a) possess surplus job qualifications (b)

has limited opportunities to acquire and use new job-related skills

(Johnson, Morrow, & Johnson, 2002). Perceived over-qualification is said

to exist when individuals perceive that they possess education, experience

and skills that exceed the required job requirements. It may stem from a

lack of promotional opportunities associated with the job, which leads to

dead ends (Green, Intosh & Vignoles, 1999).

Subjective over-qualification is literally considered to be measuring

occupation related relative deprivation, which is a self-perceived situation

of unfairly disadvantaged employment conditions or unmet job

expectations (Johnson and Johnson 1995). Although both constructs are

helpful to understand the employee behavior they serve different outcomes.

Subjective over-qualification helps to identify who is “likely to leave” the


23

organisation, whereas objective over-qualification explains who is “able”

to leave (Hoskins, 2003).

Impact of Perceived Over-Qualification

The impact of over-qualification seemed to be more dismal when it is

subjective. It has been studied that subjective over-qualification shows

more effect on work attitudes than objective over-qualification (Burris,

1983; Maynard, Joseph, & Maynard, 2006 Johnson Marrow & Johnson,

2002). The subjective feelings of over-qualification were not closely

related to educational background (Burris 1983). For some individuals,

when they feel that they had mastered over jobs wanted to try something

different. Another reason is their potential not being fully used and the

opportunity to learn and grow on the job is limited. Their feelings are also

observed to be high when working along with undereducated graduates in

the same post. Lack of training and promotional opportunities, autonomy,

constitutes another reason. The inability to apply skills and knowledge

acquired in college, the difficulty of applying the specific content which

they have learned also amount to a negative perception towards over-

qualification.

Most of the existing literature of perceived over-qualification studied its

impact on various work attitudes. The work attitudes that have been

generally studied include job satisfaction, career satisfaction,

organizational commitment, turnover and turnover intention, job crafting,

job stress, psychological wellbeing, job involvement, job acceptance

intentions etc. One extensively studied consequence of perceived over-

qualification is job dissatisfaction. It is been found that an individual who

possess a high perceived over-qualification will show a job dissatisfaction

(Herzberg, 1966; Fine & Nevo, 2008; Hoskins, 2003; Saravanabawan &


24

Uthayatharshika, 2014; Jhonson & Jhonson 1996, 2002) and will be

engaged in job search behavior and ultimately result in turnover behavior

(Maynard & Parfyonova, 2013; Wald, 2005; Maynard, Joseph, &

Maynard, 2006; Cable & Hendey, 2009/2010). Overqualified employees

are found dissatisfied with their wages, responsibilities, challenges, career

advancements and other aspects of their job. Basically the job search

behavior and turnover intention observed among overqualified employees

are partly driven by the urge to find an employment worth enough to utilize

their skills better (Feldman C. , 2011)

Johnson and Johnson (2002) studied two components of perceived over-

qualification. They were perceived lack of growth and opportunity and

perceived mismatch of individual qualifications and job requirements. It

was found that both components were significantly negatively related to

work satisfaction. Thomas Hoskins (2003) conducted a study on the

graduates of Air force institute of technology in US and found that the

perception regarding utilization of skills play a role on job satisfaction and

organizational commitment. In another study conducted by

Saravanabawan & Uthayatharshika, (2014) perceived over-qualification

was found negatively correlated with job satisfaction, affective ,

continuance commitment and positively related to turnover intention.

One immediate consequence of perceived over-qualification is found to be

turnover intention (Hersch, 1991; Johnson and Johnson, 2001, 2002; Burris

1983; Tsang, 1985 and 1987; Feldman and Turnley,1995; Sagie et al, 2002;

Maynard, Joseph, & Maynard, 2006). The dissatisfaction of overqualified

employees forms the basis behind their turnover intention. An

overeducated worker feels dissatisfied with his present job requiring lesser

skills and education. This leads to lower organizational commitment.


25

These negative attitudes form the root cause of turnover intention.

According to Sloane et al (1991), overeducated workers are likely to have

shorter tenure. The consequent attritions are to pave the way to a chain of

consequences like employee dissatisfaction ending up with organizational

inefficiency, poor service quality, high customer turnover and decreased

profitability.

Hersch (1991) conducted a study on education - job match in

manufacturing and warehouse firms and found that overqualified workers

are less satisfied with their jobs and more likely to quit. Alba- Ramirez

(1993) found that overeducated individuals experienced higher job

turnover than other comparable workers. Johnson and Johnson (1996)

recognized a negative relationship between over-qualification and

intention to stay. Johnson and Johnson (1996) explored a positive

relationship between perceived over-qualification and psychological

distress. The study was conducted among American postal workers and it

was found that greater the perceived over-qualification greater is the

psychological distress.

The Labor Market Scenario and Over-qualification in Kerala

Kerala is a State known for its investment in education and health. Kerala

model of development is characterized by high investment in education and

health that giving rise to high physical quality of life (Kothari, 1966). This

has led to Kerala achieving an unprecedented social development and

scores high on all social indicators well ahead of all the other Sates in India,

the indices of which is even comparable with developed countries. Kerala’s

achievement in education lies in high literacy rates, free and universal

primary education, low dropout rates at the school level, easy access and

gender equality. The State ranks high in human development index and


26

literacy rates among all other States in India and has made commendable

achievement in education and health. At the same time as a Paradox the

State also ranks the highest in the unemployment rate among educated

youth

A preliminary study has been conducted to enquire into the problem of

over-qualification in Kerala. It has been exposed that there is a massive

range of overqualified people in both public and private sector jobs in

Kerala. The over-qualification was found to be higher among arts and

science postgraduates, professional graduates and PhD holders. The figures

of educated unemployed are getting worse that these graduates are in fact

forced to accept any jobs that come on their way in order to prevent them

from being unemployed. A newspaper article in Indian Express (Express

News Service, 2013) reported that an increasing number of professional

graduates including IT graduates are applying for Kerala public sector

lower division clerical jobs that at least they value a secure job, regular

income and other non-monetary benefits offered by the Government jobs.

One basic reason for this phenomenon in Kerala is the expansion of higher

education due to heavy subsidization of education by government, high

expectation of today’s youth, preference for government jobs (Tilak,

2001), concentration of certain skills (Brynin, 2002) in the labor market,

demand not increasing commensurate with supply (Devasia, 2005) etc.

Some studies observed over-education to be a temporary problem

especially at the entry level and gradually disappear as the worker gains

experience and is promoted to next higher levels. But in Kerala the

experience is diverse as the worker once accepted a job seemed to get

lodged within that work. These jobs are often characterised by time bound

promotions or in some cases with no promotions. To site some examples,


27

sales girls and boys possessing degree or postgraduate qualifications in

textile shops, BTech graduates taking up jobs where a diploma

qualification is demanded, graduates ending up in jobs which are extremely

different from their line of work, MBA graduates working as door to door

sales executives etc.

The labor market context inevitably shapes the approach a firm takes to

HRM and is one of the key factors influencing HR strategic formation

(Boxall & Purcell, 2003). Central to the concept of strategic human

resource management is the idea of “fit” in Organisations. This fit

perspective is based on the classic contingency view of organizations,

which attributes success to how well organizational strategy, structure,

technology and people fit with and supports each other (Lawrence &

Lorsch, 1986) .

Thus keeping in view the consequences of perceived over-qualification, a

high time is felt to study the magnitude of perceived over-qualification in

Kerala. The basic objective of this paper is to measure perceived over-

qualification and to identify whether it embraces any sub dimensions. For

the purpose, perceived over-qualification has been operationally defined as

the extent to which an employed individual perceives that he or she

possesses surplus job qualifications, surplus skills and surplus experience.

Existing Measures of Perceived Over-qualification

Perceived over-qualification or subjective over-qualification and is

described as the workers perception about the mismatch and their feelings

associated with it. Several studies have explained that the consequence of

over-qualification is severe when the subjective over-qualification is high.

Over qualification refer to a situation of being overeducated, over-skilled,


28

over-experienced or over-intelligent among many others (Erdogan, Bauer,

Peir´o, & Truxillo, 2011). As this is the case the scales developed so far

intended to measure the perceptions of employees with respect to

utilization of their education, skills, experience knowledge etc. From an

extensive literature review it was learned that three scales were developed

so far to measure the variable. One of these scales is unidimensional, one

is two dimensional and the third is multidimensional. The researcher made

a thorough analysis of these scales with respect to the relevance of the

current study.

Details of the existing measures of perceived over-qualification are as

follows. One is the POQ scale developed by Johnson and Johnson (1996).

It is a 10-item scale incorporating 8 items developed by Khan and Marrow

(1991) and two additional items developed by Johnson and Johnson

(1996). The 10 items of the scale were grouped into two subscales namely

“Mismatch” and “No growth”. The mismatch scale points towards the

dimensions of excess education or excess skills and no growth subscale

measures perceptions of employees regarding the growth and learning

opportunities provided by the job. The limitation of this scale was that two

dimensions of POQ namely excess education and excess skills and work

experience where combined to form a single “mismatch” scale. A study

conducted by Poon (2007) regarding the dimensions and measures of

perceived over-qualification has made an analysis of various scales in

existence for measuring the construct. In his study he suggested for a

further research to test whether this conceptual separation of dimensions

could be empirically supported. Another limitation of the scale was the

uncertainty regarding whether the “no growth” subscale constituted to the


29

construct of perceived over-qualification. Moreover a lower internal

consistency was reported for the scale by several studies.

Keeping in view of the limitations of POQ scale Maynard et al (2006)

developed the scale of perceived over-qualification (SPOQ) comprising of

nine items. It is developed to measure the respondents’ perceptions about

their KSAs (knowledge, skills and abilities). It is developed as a

unidimensional scale combining the dimensions of excess education,

excess skills and work experience. Comparing with POQ scale, SPOQ

provides higher internal consistency (Poon, 2007) and encourages

respondents to use job requirement as a referent for their comparison. In

case of POQ scale the referent is not provided and the respondents are free

to use their own referents. This may provide a discrepancy in measuring

whether the respondents has addresses their response with reference to

their colleagues or job requirement or used any other referent. The

researcher used the two scales in two different pilot studies and got higher

internal consistency for SPOQ (0.84). Hence it was decided to use SPOQ

scale to measure perceived over-qualification.

Another scale known as multidimensional perceived over-qualification

(MDPOQ) was developed by (Poon, 2007) consists of 21 items with five

factors. Since there is no clarity regarding the five factors under this scale

and since it is hardly used in any studies to measure perceived over-

qualification, this scale has been ignored.

Although the SPOQ scale was developed as a unidimensional scale

measured in a five point scale ranging from 'strongly agree' to 'strongly

disagree', the scale incorporates different dimensions of perceived over-

qualification like excess education, excess skills and work experience into

a single scale. SPOQ contains nine items which measure respondents'


30

perception regarding his or her surplus education, work experience,

knowledge, skills and ability (KSA) (Poon, 2007). Along with these nine

items the researcher also added two more statements from the POQ scale

developed by Khan and Marrow to bring out exactly the perception of

employees regarding their over-qualification. Those statements were “My

formal education over-qualifies me for my present job” and “Frankly I am

overqualified for the job I hold”.

Methodology

The data has been collected from the bank employees working in

nationalized and private banks in Kerala. The population of the study is

defined as the “employees working under clerical and officer cadre” in both

nationalized and private banks. The sample size is 561. The period of data

collection was from November 2014 to April 2015. The officers and

clerical staff who are at the entry level and who progressed a shot span

through their career have been selected for the survey. This was done to

study their aspirations while completing their degree and the reasons

behind their banking career choices. The employees in the public sector

banks are placed through the IBPS examinations while some of them

belong to ex-servicemen category. A part of the employees in the private

sector are placed through campus recruitment.

This study is exploratory in nature during the first phase of the research.

Descriptive research was then adopted during the next stage of the study

which falls into a conclusive design. In public sector banks employees

working under clerical and officer cadre were surveyed.

The data has been controlled for age and job designations. This is done

because for aged employees over-qualification might not be a serious

concern. As such aged employees were not considered for the survey.


31

Instead data collection was confined only to those employees within the

age group of 21 to 40. Along with the age group job designations were also

controlled in order to survey employees doing the same nature of job in

both the organization types.

Public Sector Banks (PSBs) are banks where a majority stake (more than

50%) is held by the government. The shares of these banks are listed on

stock exchanges. There are a total of 27 public sector banks in India. They

comprises of 21 public sector banks and 6 State bank group (SBI and its 5

associates). The private sector banks in India are split into two groups by

financial regulators after the economic reforms in 1990. The old private

sector banks existed prior to the nationalization of banks in 1969 and kept

their independence because they were either too small or specialized to be

included in nationalization. The new private sector banks are those that

have gained their banking license since the liberalization in 1990s and are

incorporated as per the revised guidelines issued by the RBI regarding the

entry of private sector banks in 1993.

Results

It was observed during the survey that employees possess different

educational back gro68 unds. There were employees who completed

bachelor of technology, biotechnology, science degrees, commerce and

management degrees etc and then turned to a banking career. The job

Variable name Frequency Valid percentage

Gender

Male 315 56.1

Female 246 43.9

Total 5616 100


32

position of cleeks and officers in banks requires any bachelor degree as the

required qualification for recruitment of employees.

The sample consists of 312 males and 246 females comprising 56% and

44% respectively. The age distribution of the respondents shows that

majority belong to the age group 26-30(46%), followed by 20-25 (24%),

31-35 (21.2%), 36-40 (3.9%) and 41-45 (2.33%) respectively. 51% of the

employees are from public sector banks and 49% of the employees are

from private banks. employees surveyed, ‘officers’ constitutes 60%, clerks

26% and the sales officers 14%.

To measure objective over-qualification, the actual qualification of

employees is compared with the required qualification specified for the

jobs. Out of 561 employees surveyed, 182 (32%) employees possess a

professional post-graduation, 94 (16.8%) of them possess a post-

graduation and 93 (16.8%) of them possess a professional graduation.

Employees who possess an educational qualification above degree are

considered overqualified for the purpose of current study. Thus out of 561

employees sampled 369 employees were overqualified which constitutes

66% of the entire sample. Only 34% of the employees were found to be

adequately matched.

Descriptive Statistics-Perceived Over-qualification [POQ]

Table 1.1 Reliability Analysis of perceived over-qualification

Reliability Statistics of original data

Variables Cronbach's Alpha No: of items

Perceived over

qualification 0.905 11

Source: Survey data.


33

The reliability measure of perceived over-qualification is shown in the

table 1.1. Cronbach alpha value for POQ is 0.905 which ensures a sufficient

reliability. The descriptive statistics of POQ is provided in the table 1.2.

The mean value of POQ is 32.1 (SD= 8.55) with a lowest recorded score

of 11 and a highest recorded score of 54. The mean value of POQ obtained

is 58.4% of the maximum score.

Table 1.2.Descriptive Statistics of perceived over-qualification

The test of normalcy has been performed for perceived over-qualification

and is illustrated in the figures of Q-Q plots and histogram shown in figure

1.1. The figure shows that the observed values of perceived over-

qualification lies closer to the diagonal line and hence proves normality.

The histogram also shows that the data distribution is normal. This enables

the researcher to perform parametric tests for statistical analysis for the

variable. The box plot shows that there are no outliers. Skewness and

kurtosis are also found to lounge within the acceptable limits.

Factor analysis of Perceived over-qualification

Factor analysis is performed to explore the underlying dimensions of

perceived over-qualification. The goal of factor analysis is to reach a

parsimonious solution— one that explains the observed correlations

P

O

Q

Mean Standard

deviation

Vari

ance

Range Min Max Maximum

possible sore

Mean

%

score

32.1 8.55 82.4

9

44 11 54 55

Source: Survey data


34

Figure 1.1 Q-Q plot, histogram and box plot of POQ.

between the variables with as few factors as possible (Stoetzel, 1960).

Exploratory factor analysis has been attempted to revalidate and check the

dimensionality of the new scale formed with SPOQ scale and the two

statements added from POQ scale with all the 11 items.

Kaiser-Meyer Olkin (KMO) measure of sampling adequacy and Bartlett’s

test of sphericity were conducted to test the appropriateness of the available

data for conducting factor analysis. Table.1.3 provides the results of the

two tests conducted.

From the Table1.3 it is observed that the value of KMO is 0.896. The KMO

measure of sampling adequacy is a statistic that indicates the proportion of

variance caused by underlying factors called common variance. The values

of KMO measure of sampling adequacy varies between 0 and 1(Kaiser

1974). The values close to 1 are considered better and the threshold value

is considered to be 0.60. Since the value of KMO measure shown in the

table 1.3 is well above 0.6 it can be concluded that the data is appropriate

to apply factor analysis to reach meaningful conclusions as 90% of

common variance is explained by the underlying factors.


35

Similarly Bartlett's Test of Sphericity is used to test whether the correlation

matrix of variables is an identity matrix which shows that all the variables

are unrelated. An identity matrix is a matrix where all diagonal terms are 1

and all off diagonal terms are zeroes. From table.6.1 it can be seen that the

value of chi-square is 2689.17 significant at 1%. Hence it rejects the

hypothesis that the correlation matrix is an identity matrix and

concludes that there are underlying relationships between the variables

that may yield a pattern in the factor analysis.

After conducting the suitability tests the next procedure was attempted to

explain the total variance by extracted dimensions. It was seen that 3

factors were extracted explaining 73% of the variance (table. 1.4). The

Table1.3 KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .896

Bartlett's Test of Sphericity Approx. Chi-Square 2689.17

df 55

Sig .000

Source: survey data

Table.1.4. Total Variance Explained-POQ

Co

mp

on

ent

Initial Eigen values Extraction Sums of

Squared Loadings

Rotation Sums of

Squared Loadings

Total

Per

cen

tag

e o

f

Va

ria

nce

Cu

mu

lati

ve

Per

cen

tag

e

To

tal

Per

cen

tag

e o

f

Va

ria

nce

Cu

mu

lati

ve

Per

cen

tag

e

To

tal

Per

cen

tag

e o

f

Va

ria

nce

Cu

mu

lati

ve

Per

cen

tag

e

1 5.68 51.64 51.64 5.68 51.64 51.64 3.27 29.73 29.73

2 1.22 11.07 62.71 1.22 11.07 62.71 2.40 21.83 51.56

3 1.15 10.46 73.17 1.15 10.46 73.17 2.38 21.62 73.17

4 0.67 6.14 79.31

5 0.43 3.94 83.25

6 0.41 3.69 86.94

7 0.36 3.27 90.20

8 0.32 2.91 93.12


36

results show that Eigen values exceed one in case of three components.

Component 1 explains 29.73% of the variance, component 2 explains

51.56% of the variance and component 3 explains 73.17% of the variance

(table. 1.4).

The rotated component matrix presented in table.1.5 show the loadings of

the original variables with the new factors extracted. When the factors are

Orthogonal these factor loadings can be taken as the correlations of the

variables with the extracted factors. The variables are sorted in the order of

decreasing correlations and the correlations less than 0.6 are not shown.

The rotated component matrix shown above yields a three-factor solution

where most of the variables are found to be correlated with separate factors.

9 0.29 2.66 95.78

10 0.27 2.48 98.26

11 0.19 1.74 100.00

Extraction Method: Principal Component Analysis.

Source: Survey data

Table. 1.5 Rotated Component Matrixa

Component

Excess Education Excess Training Excess Skills

Formal education 0.862

Education level 0.803

Overqualified 0.820

Less Education 0.652

Previous training 0.823

Less experience 0.838

Work experience 0.761

Education

More abilities 0.813

Job skills 0.847

Knowledge .0.781

Extraction Method: Principal Component Analysis.

Source: Survey Data


37

Factor 1 loads four items namely:

1. “My formal education over-qualifies me for my present job”

(0.811),”

2. “My education level is above the education level required to do my

job (0.774)”,

3. “Frankly, I am overqualified for the job I hold” (0.773),

4. “Someone with less education than myself could do my job just as

well” (0.688).

Factor 2 loads three items namely:

1. “My previous training is not being fully utilized on this job”

(0.738).

2. “Someone with less experience than myself could do my job just

as well” (0.649).

3. “The work experience that I have is not necessary to be successful

on this job” (0.625).

Factor 3 loads three items namely:

1. “I have more abilities than I need in order to do my job” (0.725),

2. “I have job skills that are no required for this job” (0.698),

3. “I have a lot of knowledge that I do not need in order to do my job”

(0.618).

Factors 1, 2 and 3 were respectively named as excess education, excess

experience, and excess skills respectively. The items having factor loading

less than 0.50 shall be eliminated (Hair et al, 1996). Accordingly the item

“My job requires less education than I have” has been eliminated as it

showed a factor loading less than 0.5. Respondents might have considered

this question as disgracing themselves. Thus ten items were used to

measure perceived over qualification.


38

Confirmatory Factor Analysis (CFA) of Perceived Over-qualification

(POQ)

A confirmatory factor analysis provide information on confirmation of

measurement model

with dimensions

explored by EFA. The

fit indices received

after doing the CFA

suggested that the

measurement model

obtained is reasonably

fit. The hypothesized

model is illustrated in

figure 1.2 and the

model fit indices are presented in table1.6 It was found that the three

underlying dimensions explored namely excess education, excess skills

and excess experience are statistically valid and there are no statistical

evidences to reject the model. Examination of the loadings indicated that

the standardized regression weights for all the factors are satisfactory.

Fig. 1.6 Full measurement model of POQ

Table. 1.6. Confirmatory factor analysis of perceived over-qualification.

CMIN/D

F

NFI RFI IFI TLI CFI GFI AGF

I

RMSE

A

RM

R 3.171 0.96

8

0.95

6

0.97

8

0.96

9

0.97

8

0.96

7

0.943 0.052 0.049

Source: AMOS results of Survey Data

The model fit indices provided in table1.6 shows satisfactory results. The

CMIN/DF known as the minimum discrepancy or normed square value is

less than 5. A normed chi-square of less than 5 indicates a good fit


39

(Wheaton, Muthen, & Alwin, 1977). According to Bentler & Bonnet,

(1980), Bollen, (1990), Hu & Bentler, (1999) the base line comparison

Index values greater than 0.9 and RMSEA value less than 0.06 indicates a

good model fit. The base line comparison index values like CFI, NFI, RFI,

IFI, TLI are well above 0.9 and the RMSEA value is 0.06.Therefore with

95 percent confidence it can be inferred that the three factors better reflects

the underlying dimensions of perceived over-qualification. The factor

loadings indicated that the standardized regression weights for all the

factors are satisfactory (table 1.7).

Table1.7 Estimates of Regression Weights

Unstandardized

regression

Estimates

S.E. C.R. P Standardized

regression

Estimates

E1 <--- Exe 1 0.917

E2 <--- Exe 0.937 0.039 24.31 *** 0.794

E3 <--- Exe 0.976 0.036 27.01 *** 0.844

E4 <--- Exe 0.655 0.035 18.67 *** 0.674

S1 <--- Exs 1 0.828

S2 <--- Exs 1.022 0.051 20.19 *** 0.826

S3 <--- Exs 0.912 0.049 18.71 *** 0.761

X1 <--- Exe 1 0.844

X2 <--- Exe 0.965 0.047 20.4 *** 0.821

X3 <--- Exe 0.88 0.048 18.41 *** 0.741

Source: Survey data

Discussion

The study attempted to explore whether perceived over-qualification

(POQ) embraces any sub-dimensions so that it can be measured more

accurately. For serving the purpose POQ has been measured using nine

items developed by Maynard et al (2006) and two items borrowed from

Johnson and Johnson (1996). An exploratory factor analysis has been


40

performed in order to explore the underlying dimensions of the construct.

Three dimensions were explored namely excess education, excess skills

and excess experience explaining 73% of variance in POQ. This shows that

an employee with a high POQ is said to encompass his or hers perception

towards the excess education, skills and experience possessed by them.

This result points towards the perception of overqualified employees with

respect to their underutilized skills and abilities and the resultant

psychological state. This study added three dimensions to perceived

qualification which has been so far studied as a single dimension. Further

studies can be done to explore which of these dimensions contribute more

towards determining the work attitudes of employees.

References

Alba-Ramirez, A. (1993). Mismatch in Spanish labor

market:Overeducation? Journal of Human Resource,27(2) , 259-78.

Bentler, P. & Bonnet, D. (1980). Significance tests and goodness of fit in

the analysis of covariance: Psychological Bulletin , 88 (3), 588-606.

Berg, I. (1971). Education and jobs: The great training robbery. Newyork:

Beacon Press.

Black, D. J. (2012). Overeducation:Is it voluntary for some individuals?

The University of Melbourne, Melbourne Institute of Applied

Economic and Socil research.

Bollen, K. (1990). Overall fit in covariance structure models: Two types of

sample size effects. Psychological Bulletin , 107 (2), 256-59.

Boxall, P. F., & Purcell, J. (2003). Strategy and human resource

management. Palgrave Macmillan.

Burris, V. (1983). The social and political consequences of overeducation.

American Sociological Review , 48, 454-67.

Cable, D., & Hendey, D. (2009/2010). What to do with overqualified

candidate. Human Resoures Magazine , 14(5), 8-9,22.

Erdogan, B., Bauer, T. N., Peir´, J. M., & Truxillo, D. (2011).

Overqualified employees: Making the best of a potentially bad

situation for individuals and organizations. Industrial and


41

Organizational Psychology: Perspectives on Science and Practice ,

4, 215–232.

Feldman, C. (2011). Theoretical frontiers for underemployment research.

In D. Maynard, & D. Feldman,(edt) Underemployment:

Psychological, economic,and social challenges (277–305). New

York and Heidelberg: Springer.

Feldman, D. C. (1996). The nature, antecedents and consequences of

underemployment. Journal of Management , 22 (3), 385-407.

Feldman, D. C., & Turnley, W. H. (1995). Underemployement among

recent business college graduates. Journal of Organisation Behavior

, 16, 691-706.

Fine, S., & Nevo, B. (2008). Too smart for their own good? A study of

perceived cognitive Too smart for their own good?. The

International Journal of Human Resource Management , 19 (2)

346–355.

Green, F., McInthosh, S., & Vignoles, A. (1999). Overeducation and skills-

clarifying the concepts . Centre for Economic Performance, LSE. ,

(No. dp0435).

Hersch. (1993). Education match and job match. Review of Economics and

Statistics,73 , 140-44.

Hersch, J. (1991). Education mismatch and job mismatch. Review of

Economics and Statistics , 73 (1), 140-144.

Herzberg, F. (1966). Work and the Nature of Man. California: World Pub.

Co.

Hoskins, T. E. (2003). The effect of perceived overqualification on job

satisfaction,organizational commitment and turnover:A study of

AFIT gradautes. USA: Graduate School of Engineering and

Management,Air Force Institute of Technology.

Hu, L., & Bentler, P. (1999). Cut off criteria for fit indexes in covariance

Structure analysis: Conventional criteria. Structural Equation

Modeling , 6 (1) ,1-55.

Johnson, W. R., Morrow, P. C., & Johnson, G. J. (2002). An evaluation of

perceived overqualification scale across work settings. The Journal

of Pshycology, 136(4), 425.


42

Jones Johnson, G., & Johnson, W. R. (1995). Subjective under

employment and job satisfaction. The Journal of Social Psychology

, 25, 73-84.

Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39.

Khan, L. J., & Marrow, P. (1991). Objective and subjective under-

employment relationships to job satisfaction. Journal of Business

Resaerch , 211-218.

Kothari, D. S. (1966). Report of the Education Commission,. New Delhi:

Govt of India.

Lawrence, P. R., & Lorsch, J. (1986). Organization and environment.

Harvard Business School Classic.

Maynard, D. C., & Parfyonova, N. M. (2013). Perceived overqualification

and withdrawal behaviours: Examining the roles of job attitudes and

work values. Journal of Occupational and Organizational

Psychology , 86, 435–455.

Maynard, D. C., Joseph, T. A., & Maynard, A. M. (2006).

Underemployment, job attitudes and turnover intentions. Journal of

Organizational Behavior , 27, 509-536.

Poon, M. Y. (2007, August). Dimensions and measures of perceived

overqualification. Thesis submitted to The Chinese University of

Hong Kong.

Saravanabawan, A., & Uthayatharshika, M. J. (2014). Examining the

impact of overqualification on employees job attitudesand behavior:

Evidence from banking sector employees in Srilanka. International

Journal of Economics, Commerce and Management , Vol. 2 (5).

Express News Service. (2013). IT crowd eyeing Govt jobs City Express.

The New Indian express, 22nd August.

Stoetzel, J. (1960). A Factor Analysis of Liquor Preferences of French

Consumers. Journal of Advertising Research.

Tsang, M. C. (1987). Impact of underutilisation of education and

productivity: A case study of US Bell Companies. Economics of

education review , VI, 239-254.

Tsang, M. C., & Levin, H. M. (1985). The economics of overeducation.

Economics of Education Review , IV, 93-104.

Wheaton, B., Muthen, B., & Alwin, D. F. (1977). Assessing reliability and

stability in panel models. Sociological Methodology , 8 (1), , 84-136.

EXPLORING THE SUB DIMENSIONS OF PERCEIVED OVER …djsronline.in/Downloads/Vlolume5/2.pdf ·...

Documents

Transcript of EXPLORING THE SUB DIMENSIONS OF PERCEIVED OVER …djsronline.in/Downloads/Vlolume5/2.pdf ·...